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本文彙總了ECCV 2020上部分對抗相關論文，後續公衆號會隨緣對一些paper作解讀。感興趣的同窗，可先自行根據標題，搜索對應連接（有些paper可能未公佈）。值得注意的是，這裏的對抗包括了生成對抗GAN、以及對抗攻擊/防護，二者
概念上是迥然
的。
House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation
Regularization with Latent Space Virtual Adversarial Training
Model-Agnostic Boundary-Adversarial Sampling for Test-Time Generalization in Few-Shot learning
Multi-task Learning Increases Adversarial Robustness
Towards Automated Testing and Robustification by Semantic Adversarial Data Generation
Adversarial Generative Grammars for Human Activity Prediction
TopoGAN: A Topology-Aware Generative Adversarial Network
Studying the Transferability of Adversarial Attacks on Object DetectorsSpotlight
1915Multimodal Shape Completion via Conditional Generative Adversarial Networks
CPGAN: Content-Parsing Generative Adversarial Networks for Text-to-Image Synthesis
Adversarial T-shirt! Evading Person Detectors in A Physical World
Counterfactual Vision-and-Language Navigation via Adversarial Path Sampler
Adversarial Self-Supervised Learning for Semi-Supervised 3D Action Recognition
Improved Adversarial Training via Learned Optimizer
Domain-Specific Mappings for Generative Adversarial Style Transfer
Unpaired Image-to-Image Translation using Adversarial Consistency Loss
Dual Adversarial Network: Toward Real Noise Removal and Noise Generation
Adversarial Continual Learning
Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses
AMLN: Adversarial-based Mutual Learning Network for Online Knowledge Distillation
AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds
Bias-based Universal Adversarial Patch Attack for Automatic Check-out
SemanticAdv: Generating Adversarial Examples via Attribute-conditioned Image Editing
Symbiotic Adversarial Learning for Attribute-Based Person Search
Adversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization
Multi-level Wavelet-based Generative Adversarial Network for Perceptual Quality Enhancement of Compressed Video
Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation
Adversarial Ranking Attack and Defense
Boosting Decision-based Black-box Adversarial Attacks with Random Sign Flip
Design and Interpretation of Universal Adversarial Patches in Face Detection
Open-set Adversarial Defense
Robust Tracking against Adversarial Attacks
Semantic Equivalent Adversarial Data Augmentation for Visual Question Answering
Adversarial Semantic Data Augmentation for Human Pose Estimation
Motion-Excited Sampler: Video Adversarial Attack with Sparked Prior
Incorporating Reinforced Adversarial Learning in Autoregressive Image Generation
APRICOT: A Dataset of Physical Adversarial Attacks on Object Detection
S
parse Adversarial Attack via Perturbation Factorization
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting
DeepLandscape: Adversarial Modeling of Landscape Videos
Connecting the Dots: Detecting Adversarial Perturbations Using Context Inconsistency
Square Attack: a query-efficient black-box adversarial attack via random search
BIRNAT: Bidirectional Recurrent Neural Networks with Adversarial Training for Video Snapshot Compressive Imaging
Mind the Discriminability: Asymmetric Adversarial Domain Adaptation
Dual Adversarial Network for Deep Active Learning
Adversarial Training with Bi-directional Likelihood Regularization for Visual Classification
Improving Query Efficiency of Black-box Adversarial Attack
Efficient Adversarial Attacks for Visual Object Tracking
Adversarial Robustness on In- and Out-Distribution Improves Explainability
Multi-Source Open-Set Deep Adversarial Domain Adaptation
Improving Adversarial Robustness by Enforcing Local and Global Compactness
TopoGAN: A Generative Adversarial Approach to Topology-Aware Road Segmentation
Discriminative Partial Domain Adversarial Network
Unsupervised Monocular Depth Estimation for Night-time Images using Adversarial Domain Feature Adaptation
Defense Against Adversarial Attacks via Controlling Gradient Leaking on Embedded Manifolds
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations
Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks
Dual Mixup Regularized Learning for Adversarial Domain Adaptation
Adversarial Data Augmentation via Deformation Statistics
Manifold Projection for Adversarial Defense on Face Recognition
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